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CCS
2010
ACM
13 years 5 months ago
TASTY: tool for automating secure two-party computations
Secure two-party computation allows two untrusting parties to jointly compute an arbitrary function on their respective private inputs while revealing no information beyond the ou...
Wilko Henecka, Stefan Kögl, Ahmad-Reza Sadegh...
CORR
2010
Springer
144views Education» more  CORR 2010»
13 years 5 months ago
Privacy-Preserving Protocols for Eigenvector Computation
Abstract. In this paper, we present a protocol for computing the principal eigenvector of a collection of data matrices belonging to multiple semi-honest parties with privacy const...
Manas A. Pathak, Bhiksha Raj
PAISI
2010
Springer
13 years 3 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...